Description

Key Responsibilities

• Define end-to-end solution architectures including system components, integrations, data flows, and technology stacks

• Produce conceptual, logical, and physical architecture designs aligned with enterprise architecture standards

• Design scalable, secure, cloud-first solutions using modern architecture patterns (APIs, microservices, event-driven)

• Lead AI/ML solution architecture design including LLM integration, data pipelines, deployment models, monitoring, and responsible AI controls

• Evaluate and recommend platforms, technologies, SaaS/COTS solutions, and vendors based on fit-for-purpose analysis

• Facilitate architecture and design workshops with technical and non-technical stakeholders

• Act as a trusted technical advisor to project leaders, governance bodies, and executive stakeholders

• Ensure compliance with security, privacy, accessibility, and regulatory requirements

• Apply responsible AI principles including bias mitigation, explainability, governance, and model monitoring

• Identify and manage technical risks, dependencies, and architectural trade-offs

• Contribute to architecture governance forums, communities of practice, and technical review groups

• Provide implementation guidance and architectural assurance throughout delivery

• Lead proof-of-concept initiatives for AI/ML and emerging technologies

• Produce high-quality architecture documentation, decision records, and reusable reference patterns

• Support legacy system migrations including transition states, data migration strategies, and cutover planning

Required Skills & Experience

5+ years’ experience as a Solution Architect, Lead Architect, or equivalent senior technical role

• Proven experience designing enterprise-scale solutions across multiple technology domains

• Strong knowledge of architecture frameworks and design patterns (e.g. TOGAF)

• Hands-on experience with cloud platforms (AWS, Azure, or GCP)

• Expertise in modern integration and architecture paradigms (APIs, microservices, event-driven systems)

• Strong background in data architecture, data governance, and enterprise data management (DAMA principles)

• Solid understanding of security architecture, identity, access management, and data protection

• Experience with DevOps practices, CI/CD pipelines, and infrastructure as code

• Working knowledge of AI/ML architecture patterns including LLMs, data pipelines, and AI service integration

• Experience applying responsible AI practices, governance frameworks, and ethical AI principles

• Excellent communication skills with the ability to present complex technical concepts clearly

• Proven ability to influence stakeholders and build consensus across organisational boundaries

• Experience supporting project planning, estimation, and risk management

• Ability to manage multiple concurrent initiatives and competing priorities

Key Skills

Education

Any Graduate